Given an input vector of the form “signal + iid Gaussian noise”, the function estimates the noise level via Median Absolute Deviation, finds the best bottom-up Unbalanced Haar decomposition, thresholds it with the universal threshold, and performs the inverse Unbalanced Haar transform to yield an estimate of the signal.
a vector of the form “signal + iid Gaussian noise”
at each iteration, only the first
an estimate of the signal
P. Fryzlewicz (2007) “Unbalanced Haar technique for nonparametric function estimation”. Journal of the American Statistical Association, 102, 1318-1327.
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